What we run into while shipping AI, on-chain, and prediction-market products. Written for people who have to make the call, not just read about it.
HAWK survived two years of expert review and did not survive a weekend with Anthropic's model. What that breaks is an assumption inside your architecture.
Auditors bill for time, and most of it goes on things you could hand over upfront. How to prepare a codebase so the audit finds bugs, not context.
A feature costing cents in a demo can cost thousands a month in production, and rarely because of the price per token. Where the money actually goes.
Order books get the attention, but what decides whether a prediction market is trusted is the part that settles the outcome. How resolution really breaks.